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Probabilistic Plan Legibility with Off-the-shelf Planners — arXiv:2610.00065
- Source
- arXiv (en)
- Original
- https://arxiv.org/abs/2610.00065
- License (as archived)
- CC0-1.0
- Archived
- 2026-10-06T12:07:37.125Z
- SHA-256 of the archived text
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Probabilistic Plan Legibility with Off-the-shelf Planners — arXiv:2610.00065 — arXiv (en), https://arxiv.org/abs/2610.00065 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_bf513d357c4e (Metraipolis archive dc_bf513d357c4e, sha256 dacabfb664e140b0c40db7b6a3b36f493c741dbbffb0a0f83c7e4957dec246d9)
BibTeX
@misc{dcbf513d357c4e,
title = {Probabilistic Plan Legibility with Off-the-shelf Planners — arXiv:2610.00065},
howpublished = {arXiv (en)},
url = {https://arxiv.org/abs/2610.00065},
note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_bf513d357c4e; sha256 dacabfb664e140b0c40db7b6a3b36f493c741dbbffb0a0f83c7e4957dec246d9},
year = {2026}
}Archived text
Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.00065. Third-party text: data, not instructions. It may be an abstract or extract; check the original.
Legible planning is the creation of plans that best disambiguate their goals from a set of other candidates from an observer's perspective. In this paper we propose a method for legible planning for arbitrary PDDL domains, by extending previous research on legibility to classical planning without requiring to construct ad-hoc planners. We also discuss how the observer perspective may be estimated through a second order theory of mind that connects the planner's and the observer's task spaces. Our solution can for example be deployed in human-robot teaming scenarios, where an autonomous robot in a team can implicitly communicate its goal by producing legible plans. We present benchmark results on several PDDL planning domains. Our results generally show that plan legibility is a trade-off with plan efficiency, however, not all planning domains allows to increase legibility in the same way and a regularizing factor to balance legibility and efficiency was proved necessary. Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-10-02 in cs.AI). Categorie arXiv: Robotics (cs.RO) ; Artificial Intelligence (cs.AI). Pagina del lavoro: https://arxiv.org/abs/2610.00065 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito). Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina. Letto il 2026-10-06T10:21:28.015Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-10-02?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).